AI - Based Framework for Private Cloud Computing

Artificial Intelligence (AI) systems are computational simulations that are "trained" using information and expert input to duplicate a professional's choice given the same data. Only using one private cloud storage service to store information can cause a variety of issues for the system administrator. Knowledge providers, scalability, efficiency, privacy, and the potential of vendor support are examples of such concerns. Distributing information across several cloud storage services, comparable to how data is dispersed between various physical disk drives to increase error detection and increase productivity, is a possible approach. Moreover, because multiple private cloud providers have varying pricing strategies and service quality, maximizing the efficiency and profitability of many cloud providers at the same time is difficult. Based on access permission behaviors, this study presents a methodology for dynamically modifying network management rules across several cloud providers. The goal of this research is to look into how to reduce both the estimated cost and delay periods for numerous cloud providers. The architecture was put into practice in a cloud storage systems emulator, which simulated the complexity and effectiveness of numerous cloud providers in a real-world context. In particular, the architecture was evaluated in a variety of cloud storage environments. The outcomes of the platform's testing revealed that many cloud methods were successful.

Compute functional analysis leveraging the IAAS private cloud computing service model in packstack development

Analyzing compute functions by utilizing the IAAS model for private cloud computing services in packstack development is one of the large-scale data storage solutions. Problems that often occur when implementing various applications are the increased need for server resources, the monitoring process, performance efficiency, time constraints in building servers and upgrading hardware. These problems have an impact on long server downtime. The development of private cloud computing technology could become a solution to the problem. This research employed Openstack and Packstack by applying one server controller node and two servers compute nodes. Server administration with IAAS and self-service approaches made scalability testing simpler and time-efficient. The resizing of the virtual server (instance) that has been carried out in a running condition shows that the measurement of the overhead value in private cloud computing is more optimal with a downtime of 16 seconds.

Web Storage Berbasis Private Cloud Menggunakan Enkripsi SHA1 Pada GBKP Km 8 Padang Bulan Medan

GBKP km 8 Padang Bulan Medan mempunyai kendala dalam memonitor, mengatur, dan mengelola data secara cepat, efektif dan efisien, yang selama ini masih bersifat konvensional sehingga mengakibatkan tingginya biaya operasional. Pembangunan aplikasi web storage berbasis private cloud, dimaksudkan untuk menjawab kesulitan di atas. Konsep private cloud computing harus mengedepankan faktor keamanan file-file yang disimpan pada server private cloud tersebut dengan menggunakan salah satu algoritma yakni SHA1. SHA1 digunakan sebagai autentikasi, integritas dan digital signature. Akses terhadap web storage melalui koneksi intranet secara Local Area Network.